{"id":"W6924822196","doi":"10.15468/dl.mlyb72","title":"Occurrence Download","year":2019,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); Reference data; Identification (biology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009019024,0.001855068,0.001499675,0.004599198,0.0009673112,0.002353471,0.002758438,0.002080555,0.1461956],"category_scores_gemma":[0.005933083,0.0008438544,0.001165033,0.008766988,0.0004516653,0.002266853,0.002560847,0.001927246,0.2035666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001524559,"about_ca_system_score_gemma":0.002159522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0206923,"about_ca_topic_score_gemma":0.03428061,"domain_scores_codex":[0.9990819,0.0001300106,0.0001208283,0.0003238482,0.000194302,0.0001491816],"domain_scores_gemma":[0.9977487,0.0006533962,0.000202054,0.0006076532,0.0005420263,0.0002461222],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003126803,0.0000126057,0.0004550533,0.0005966103,0.0000160987,0.00001697089,0.00002782251,0.0001527995,0.0001282357,0.0003798999,0.9965081,0.001674515],"study_design_scores_gemma":[0.00007389938,0.000009429524,0.001988852,0.0002170553,0.00001539933,0.00004064751,0.00008865608,0.0002048999,0.0001851371,0.0007842354,0.9963749,0.00001694279],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005498486,0.00003247658,0.00005186842,0.00004148647,0.0000152723,0.000006248699,0.9986905,0.0004482402,0.0006587749],"genre_scores_gemma":[0.0001940477,0.00003615374,0.000224823,0.00004819835,0.000003760253,0.00004435153,0.9988523,0.0001451696,0.0004512474],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8538044,"threshold_uncertainty_score":0.489073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0225412765836933,"score_gpt":0.2352696232258381,"score_spread":0.2127283466421448,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}